Students' performance in interactive environments: an intelligent model [PeerJ]
Por um escritor misterioso
Last updated 05 julho 2024
![Students' performance in interactive environments: an intelligent model [PeerJ]](https://dfzljdn9uc3pi.cloudfront.net/2023/cs-1348/1/fig-1-full.png)
Modern approaches in education technology, which make use of advanced resources such as electronic books, infographics, and mobile applications, are progressing to improve education quality and learning levels, especially during the spread of the coronavirus, which resulted in the closure of schools, universities, and all educational facilities. To adapt to new developments, students’ performance must be tracked in order to closely monitor all unfavorable barriers that may affect their academic progress. Educational data mining (EDM) is one of the most popular methods for predicting a student’s performance. It helps monitoring and improving students’ results. Therefore, in the current study, a model has been developed so that students can be informed about the results of the computer networks course in the middle of the second semester and 11 machine algorithms (out of five classes). A questionnaire was used to determine the effectiveness of using infographics for teaching a computer networks course, as the results proved the effectiveness of infographics as a technique for teaching computer networks. The Moodle (Modular Object-Oriented Dynamic Learning Environment) educational platform was used to present the course because of its distinctive characteristics that allow interaction between the student and the teacher, especially during the COVID-19 pandemic. In addition, the different methods of classification in data mining were used to determine the best practices used to predict students’ performance using the weka program, where the results proved the effectiveness of the true positive direction of functions, multilayer perceptron, random forest trees, random tree and supplied test set, f-measure algorithms are the best ways to categories.
Layer-by-Layer Analysis of In Vitro Skin Models
![Students' performance in interactive environments: an intelligent model [PeerJ]](http://www.scielo.org.za/img/revistas/sajhe/v35n2/12f01.jpg)
Students' perceptions of learning, using interactive notes
![Students' performance in interactive environments: an intelligent model [PeerJ]](https://ars.els-cdn.com/content/image/1-s2.0-S2667241323000198-ga1.jpg)
Generative artificial intelligence in the metaverse era - ScienceDirect
![Students' performance in interactive environments: an intelligent model [PeerJ]](https://www.mdpi.com/sustainability/sustainability-15-14780/article_deploy/html/images/sustainability-15-14780-g001.png)
Sustainability, Free Full-Text
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A bibliometric and scientometric review of research on crowdsourcing in smart cities - Jiang - 2023 - IET Smart Cities - Wiley Online Library
![Students' performance in interactive environments: an intelligent model [PeerJ]](https://dfzljdn9uc3pi.cloudfront.net/2022/cs-986/1/fig-5-small.jpg)
A systematic review on machine learning models for online learning and examination systems [PeerJ]
![Students' performance in interactive environments: an intelligent model [PeerJ]](https://dfzljdn9uc3pi.cloudfront.net/2023/cs-1256/1/fig-2-full.png)
A novel intelligent agent-based framework for appropriate stream selection from perceptive of career counseling [PeerJ]
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ProtInteract: A deep learning framework for predicting protein–protein interactions - Computational and Structural Biotechnology Journal
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Social Sciences, Free Full-Text
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